Your AI and data partner for strategy, implementation, and infrastructure
We are your strategic secret weapon, helping you moneyball your way to your biggest goals. We are the only studio run by operators that can consistently deliver your ambitions. Below is the work we do, each with the case studies behind it.
What we do
ML and AI readiness
Before you fund a machine learning model, we test whether your historical data can support one. We review the processes and metrics you want to automate, assess and clean your data, and give you an honest answer: build now, or wait, with a roadmap for when the data is ready.
Proof
- Is sales forecasting machine learning-ready...or not? Acorn recommended waiting to deploy a predictive model, because the sales team did not have enough historical data to inform a reliable tool.
Data, dashboards and predictive models
Dashboards, scorecards and shared metric baselines that give a team one version of the numbers, and predictive models built on the data you have.
Proof
- Cloud migration Dashboards, a migration scorecard and shared metric baselines for a publicly traded global B2B SaaS company.
- Churn model A model that correctly identified a customer who will churn 85-90% of the time.
- Brand business case Automated dashboards alongside a C-suite strategy framework.
- Sales forecasting and ML readiness Also an ML and AI readiness example, see above.
Custom systems and integration
Systems built to fit how your team works, including testing platforms, data migrations, and API layers that connect your systems.
Proof
- Product testing platform A testing platform and automated error troubleshooting through a mobile app for a consumer healthtech and CPG company (B2C).
- LMS migration User and course data migration, an API layer with per-client access control and usage reporting, and custom LMS endpoints for a non-profit focused on child safety that also operates in legal tech and education.
“Working with Mike and Acorn and the team has been fantastic that they really took the time to understand our business requirements. ... having that opportunity to work with Mike and the team to develop and go through that discovery process around designing a new technology platform, you know, which is fantastic for us that is scalable and flexible ...”
Data, ML and cloud operations
DataOps and data engineering, DevOps, MLOps, and cloud infrastructure, run as one practice. We deploy into production, operationalize the work, transfer competency to your team, and then move into maintenance mode.
Proof
- Product testing platform A testing platform and automated error troubleshooting through a mobile app for a consumer healthtech and consumer packaged goods company, built after key team members left before launch.
- Sales forecasting and ML readiness Our data scientists cleaned up the historical sales data, and Acorn recommended waiting to deploy a predictive model because there was not enough of it.
- Churn model A model that correctly identified a customer who will churn 85-90% of the time.
- Cloud migration Dashboards, a migration scorecard and shared metric baselines for a publicly traded global B2B SaaS company moving customers from on-premise to the cloud.
- Creating a Better Forecast with QA and Burndown Charts An illustrative walk-through of human QA checks and burndown charts that showed the real delivery date of a software project that kept missing its deadlines.
Delivery rescue and project recovery
When a project is stalled, behind, or short a team, we step in with the delivery practices that get it moving again. These three video walkthroughs each cover one engagement.
Proof
- Staggered Sprints For the Win For a light finishing trades construction products and services provider: a staggered rollout of team members that got a 1.0 delivered, with more delivered after that.
- Course Correcting with Burn Up Charts For a consumer healthtech and IoT company: a stalled team that was not covering its costs exceeded break-even, and the client had a successful conference.
- Creating a Better Forecast with QA and Burndown Charts For a construction trades company: a key stakeholder's frustrations about repeated missed deadlines solved with a chart and good QA practices.
“Mike has an amazing ability to simplify complex problems into their core elements and address the root cause of challenges rather than the apparent symptoms. He can turn scattered thoughts into discernable action plans and can make sense of even the most complicated mess of priorities. I would welcome the opportunity to work with Mike again...”
Frequently asked questions
How does an engagement start?
With a conversation about what you are building, fixing or deciding. From there we scope the engagement that fits. New clients can start with Advisory or Execution. If you are ready to commit, we scope that with you.
Do we have to clean up our procedures, data, or systems first?
No. The first thing we do is get a sense of the breadth of your systems from a high level, using automated methods. We want to avoid sending humans down tedious rabbit holes to prepare documentation that frankly should be handled in a different way. And frankly, computers are often much, much better at data cleaning than the humans are.
Will the AI change records in our accounting or case systems?
Not at first. We recommend the system read the data and report on it, while corrections are still made by a person in the source system. You can widen that later.
See what this looks like for your team.
Tell us what you are building, fixing, or trying to decide. We scope the right engagement. You can start with Advisory or Execution.
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